/*
 * Copyright (c) 2017-present, CV4J Contributors.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package com.cv4j.core.filters;

import com.cv4j.core.datamodel.ImageProcessor;

import java.util.Optional;

/**
 * 白色图像过滤器
 *
 * @author dev
 * @date 2021/07/22
 */
public class WhiteImageFilter extends BaseFilter {
    private double beta;

    /**
     * 白色图像过滤器
     */
    public WhiteImageFilter() {
        this.beta = 1.1;
    }

    /**
     * 得到β
     *
     * @return double
     */
    public double getBeta() {
        return beta;
    }

    /**
     * 设置测试
     *
     * @param beta β
     */
    public void setBeta(double beta) {
        this.beta = beta;
    }

    /**
     * 做的过滤器
     *
     * @param src src
     * @return {@link Optional<ImageProcessor>}
     */
    @Override
    public Optional<ImageProcessor> doFilter(ImageProcessor src) {
        // make LUT
        int[] lut = new int[256];
        for (int i = 0; i < 256; i++) {
            lut[i] = imageMath(i);
        }
        int index = 0;
        for (int row = 0; row < height; row++) {
            for (int col = 0; col < width; col++) {
                index = row * width + col;
                RED[index] = (byte) lut[RED[index] & 0xff];
                GREED[index] = (byte) lut[GREED[index] & 0xff];
                BLUE[index] = (byte) lut[BLUE[index] & 0xff];
            }
        }
        return Optional.ofNullable(src);
    }

    /**
     * 图像的数学
     *
     * @param gray 灰色的
     * @return int
     */
    private int imageMath(int gray) {
        double scale = 255 / (Math.log(255 * (this.beta - 1) + 1) / Math.log(this.beta));
        double p1 = Math.log(gray * (this.beta - 1) + 1);
        double np = p1 / Math.log(this.beta);
        return (int) (np * scale);
    }
}
